Publications

Refereed Journal Publications:

M. Kohler, A. Krzyzak and H. Walk, Optimal global
rates of convergence for nonparametric regression with unbounded
data, submitted to Journal of Statistical Planning and
Inference, July 1, 2005. Under revision.

M. Kohler and A. Krzyzak, Asymptotic confidence
intervals for Poisson regression. To appear in Journal of Multivariate
Analysis. Accepted July 26, 2006.

 K. Thirulogasanthar, A. Krzyzak, and Q. D. Katatbeh,
Quaternionic vector coherent states and the SUSY harmonic
oscillator. To appear in  Theoretical and Mathematical Physics Journal.
Accepted 23 March, 2006.

 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Invariant ridgelet-Fourier descriptor for pattern recognition,
 Pattern Analysis and Applications Journal, vol. 9, pp. 83-93, 2006.

 S. Li, T. Fevens, A. Krzyzak, and S. Li,
Automatic clinical image segmentation using pathological
modelling, PCA and SVM,  Engineering Applications in
Artificial Intelligence Journal, vol. 19, pp. 403-410, 2006.

 S. Li, T. Fevens, A. Krzyzak, and S. Li,
Automatic variational level set segmentation framework for dental
X-rays analysis in clinical environments,  Computerized
Medical Imaging and Graphics, vol. 30, pp. 65-74, 2006.

 M. Kohler and A. Krzyzak,
Adaptive regression estimation with multilayer
feedforward neural networks,
 Journal of Nonparametric Statistics, vol. 17, no. 8,
Dec. 2005, pp. 891-913.

 M. Kohler, A. Krzyzak and H. Walk, Rates of convergence
for partitioning and nearest neighbor regression estimates with
unbounded data,  Journal of Multivariate Analysis, vol. 97,
issue 2, Feb. 2006.

 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Rotation invariant pattern recognition using ridgelets, wavelet
cycle-spinning and Fourier features,  Pattern Recognition
Journal, vol. 38, pp. 2314-2322, 2005.


 J. Dong, A. Krzyzak, and C. Y. Suen,
An improved handwritten Chinese character recognition system using
support vector machine,  Pattern Recognition Letters, vol.
26, pp. 1849-1856, 2005.


 A. Krzyzak and M. Partyka, Global identification of nonlinear
Hammerstein systems by recursive kernel approach,  Journal on
Nonlinear Analysis, vol. 63, no. 5-7, pp. 1263-1272, 2005.

 E. Rafajlowicz and A. Krzyzak, Nonparametric and
nonlinear reconstruction of surfaces from qualitative
observations,  Journal on Nonlinear Analysis, vol. 63, no.
5-7, pp. 1273-1279, 2005.


 A. Krzyzak and D. Schaefer, Nonparametric
regression estimation by normalized radial basis function
networks,  IEEE Transactions on Information Theory, vol. 51,
no. 3, pp. 1003-1010, 2005.

 J. Dong, A. Krzyzak, and C. Y. Suen,
Fast SVM training algorithm with decomposition on very large
training sets,  IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 27, no. 4, pp. 603-618, 2005.


 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Image denoising using neighborhood wavelet coefficients,
 Integrated Computer-Aided Engineering Journal, vol. 12, no. 1,
pp. 99-107, 2005.


 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Image denoising with neighbor dependency
and customized wavelet and threshold,
 Pattern Recognition Journal, vol. 38, pp. 115-124,
2005.


 K. Thirulogasanthar, G. Honnouvo, and A. Krzyzak,
Multi-matrix vector coherent states,  Annals of Physics, vol.
314, no. 1, pp. 119-144, 2004.

 M. Pawlak, E. Rafajlowicz, and A. Krzyzak,
Post-filtering versus pre-filtering for signal recovery from noisy
samples,  IEEE Transactions on
Information Theory, vol. 49, no. 12, pp. 3195-3212, 2003.

 M. Kohler, A. Krzyzak, and H. Walk,
Strong consistency of automatic kernel regression estimates,
 Annals of the Institute of
Statistical Mathematics, vol. 55, no. 2, pp. 287-308, 2003.

 J. Dong, A. Krzyzak, and C. Y. Suen,
A fast SVM training algorithm,
 International Journal of Pattern Recognition
and Artificial Intelligence, vol. 17, no. 3, pp. 367-384, 2003.


 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Contour-based handwritten numeral recognition using
multiwavelets and neural networks,
 Pattern Recognition Journal,
vol. 36, pp. 1597-1604, 2003.


 L. Devroye and A. Krzyzak,
New multivariate product density estimators,  Journal of
Multivariate Analysis, vol. 82, pp. 88-110, 2002.

 J. Dong, A. Krzyzak, and C. Y. Suen,
Local learning framework for
handwritten character recognition,
 Engineering Applications in Artificial Intelligence Journal ,
vol. 15, no. 2, pp. 151-159, 2002.


 M. Kohler, A. Krzyzak, and D. Schaefer, Application
of structural risk minimization to multivariate
smoothing spline regression estimates,
Bernoulli Journal, vol. 8, no 4, pp. 475-489,
2002.


 J. Zhou, A. Krzyzak, and C.Y. Suen,
Verification - a method of
enhancing the recognizers of isolated and touching
handwritten numerals, Pattern Recognition Journal, vol. 35, no 5,
pp. 1179-1189, May 2002.


B. Kegl and A. Krzyzak,
Piecewise linear skeletonization using principal curves,  

IEEE Transactions on Pattern Analysis and Machine Intelligence, 

vol. 24, no. 1, pp. 59-74, Jan. 2002.

 M. Kohler, and A. Krzyzak, 

A Vapnik-Chervonenkis approach to penalized least squares estimation,  

IEEE Transactions on Information Theory, vol. 47, no. 7, pp. 3054-3058, Nov. 2001.


A. Krzyzak, 

Nonlinear function learning using optimal radial basis function networks,  

Journal on Nonlinear Analysis, vol. 47, pp. 293-302, 2001.

 A. Krzyzak, and H. Niemann, 

Convergence and rates of convergence of radial basis  functions networks in function learning,  

Journal on Nonlinear Analysis, vol. 47, pp. 281-292, 2001.

 A. Krzyzak, E. Rafajlowicz and
E. Skubalska-Rafajlowicz,
Clipped median and space-filling curves in image filtering,  

Journal on Nonlinear Analysis, vol. 47, pp. 303-314, 2001.


 A. Krzyzak, J. Sasiadek and B. Kegl,
Identification of dynamic nonlinear systems using the Hermite series approach, 

 International Journal of Systems Science, vol. 32, no. 10, pp. 1261-1285, 2001.

B. Kegl, A. Krzyzak, T. Linder, and K. Zeger, 

Learning and design of  principal curves,  

IEEE Transactions on Pattern   Analysis and Machine Intelligence, 

vol. 22, no. 3, pp. 281--297, 2000.

 J. Zhou, Q. Gan, A. Krzyzak, and C.Y. Suen, Quantum Neural

Network in Recognition of Handwritten Numerals,  

International Journal on Document Analysis and Recognition, vol. 2,

pp. 30-36, 1999.

 L. Devroye and A. Krzyzak,

On the Hilbert kernel density estimate,  Statistics

  and Probability  Letters, vol. 44, pp. 299-308, 1999.

 L. Devroye, L. Gyorfi, and A. Krzyzak,

The Hilbert kernel regression estimate,  Journal of Multivariate

Analysis, vol. 65, pp. 209-227, 1998.

A. Krzyzak and T. Linder,  Radial

basis function nets and complexity regularization in function learning,

IEEE Transactions on Neural Networks, vol. 9, no. 2, pp. 247-256, 1998.

 A. Krzyzak, E. Rafajlowicz,  and M. Pawlak,

Moving average restoration of band-limited signals from noisy observations,

IEEE Transactions on Signal Processing, vol. 45, no. 12, pp. 2967-2976, 1997.

M. Pawlak, E. Rafajlowicz, and A. Krzyzak,

Exponential weighting algorithms for restoration of band-limited signals,  

IEEE Transactions on Signal Processing, vol. 44, no. 3, pp. 538-545, 1996.

 A. Krzyzak, T. Linder,  and G. Lugosi, 

Nonparametric estimation and classification using radial basis function nets and empirical risk minimization,  

IEEE Transactions on Neural Networks, vol. 7, no. 2, pp. 475-487, 1996.

 A. Krzyzak,

On nonparametric estimation of nonlinear systems by the Fourier series estimates, 

Signal Processing Journal, vol. 52, pp. 299-321, 1996.

 L. Devroye, L. Gyorfi, A. Krzyzak, and G. Lugosi,

On the strong universal consistency of nearest neighbor regression function estimates,  

Annals of Statistics, vol. 22, no. 3, pp. 1371-1385, 1994.

 A. Cichocki, R. Unbehauen, and A. Krzyzak,

Neural networks with on-chip learning for robust estimation of principal components in real time,

Journal of Artificial Neural Systems, vol. 1, no. 1, pp. 1-23, 1994.

 L. Xu, A. Krzyzak, and A. Yuille,

On radial basis function net and kernel regression: approximation ability, convergence rate and receptive field size,

 Neural Networks Journal, vol. 7, no. 4, pp. 609-628, Sept. 1994.

 X. Yu, T.D. Bui, and  A. Krzyzak,

Range image segmentation and fitting by residual consensus,

 IEEE Transactions on Pattern Analysis and Machine Intelligence,

vol. 16, no. 5, pp. 530-538, May 1994.

 L. Xu, A.  Krzyzak, and C.Y. Suen,

Associative switch for combining multiple classifiers,

 Journal of Artificial Neural Networks, vol. 1, no. 1, pp. 77-100,  1994.

 A. Krzyzak,

Identification of nonlinear block-oriented systems by the recursive kernel regression estimate,

 Journal of the Franklin Institute, vol. 330, no. 3, pp. 605-627, 1993.

 L. Xu, A. Krzyzak, and E. Oja,

Rival penalized competitive learning for clustering analysis, RBF net and curve detection,

 IEEE Transactions on Neural Networks, vol. 4, no. 4, pp. 636-649, July 1993.

 A. Krzyzak,

Identification of nonlinear systems by recursive kernel regression estimates,

 International Journal of Systems Science, vol. 24, no. 3, pp. 577-598, 1993.

 A. Krzyzak and M. Partyka,

Identification of block oriented systems by nonparametric techniques,

 International Journal of Systems Science, vol. 24, no. 6, pp. 1049-1066, 1993.

 A. Al-Aloosy., A. Krzyzak and W. Zamojski,

Approximation of a mean time of the slot transfer in the Cambridge ring,

 Applied Mathematics and Computer Science Journal, vol. 2, no. 2, pp. 237-249, 1992.

 A.  Krzyzak,

Global convergence of the recursive kernel regression estimate with applications in classification and nonlinear time series estimation,  

 IEEE Transactions on Information Theory, vol. IT-38, no. 4, pp. 1323-1338, July 1992.

 L. Xu, A. Krzyzak,  and C.Y. Suen,

Methods of combining multiple classifiers and their applications to handwriting recognition,

 IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-22, no. 3, pp. 418-435, May/June 1992.

 L. Xu, A. Krzyzak, and E. Oja,

Neural Nets for Dual Subspace Pattern Recognition Method,

 International Journal of Neural Systems, vol. 2, no. 3, pp. 169-184, 1991.

 A. Krzyzak,

On exponential bounds on the Bayes risk of the kernel classification rules,

IEEE Transactions on Information Theory, vol. IT-37, no. 3, pp. 490-499, May 1991.

A. Krzyzak,

On estimation of a class of nonlinear systems by the kernel

regression estimate,

 IEEE Transactions on Information Theory, vol. IT-36, no. 1, pp. 141-152, January 1990.

 A. Krzyzak,

On identification of discrete Hammerstein systems by the trigonometric series regression estimates,

 International Journal of Systems Science, vol. 20, no. 9, pp. 1729-1744, 1989.

 L. Devroye and A. Krzyzak,

An equivalence theorem for L1 convergence of  the kernel regression estimate,

 Journal of Statistical Planning and Inference, vol. 23, pp. 71-82, 1989.

A. Krzyzak, Y.S. Leung,  and C.Y. Suen,

Reconstruction of two dimensional patterns by Fourier descriptors,  

Machine Vision and Applications Journal,  vol. 2, no. 2, pp. 123-140, 1989.

 A. Krzyzak,  and  M. Partyka,

Decision tables in composition and decomposition of fundamental operations in the innovation process,

 AMSE Review, vol. 5, no. 4, pp. 25-30, 1987.

 A.  Krzyzak and M. Pawlak,

The pointwise rate of convergence of the kernel regression estimate,  

Journal of Statistical Planning and Inference, vol. 16, pp. 159-166, 1987.

A. Krzyzak,

The rates of convergence of kernel regression estimates and classification rules,

IEEE Transactions on Information Theory, vol. IT-32, no. 5, pp. 668-679, 1986.

A. Krzyzak,

Distribution-free consistency and the rate of convergence of k-NN

regression estimates,  

Mittenkungsblatt der Osterrechischen Statistischen Gesellschaft, vol. 55/56, pp. 183-196, 1984.

 W. Greblicki, A.  Krzyzak,  and M.  Pawlak,

Distribution-free pointwise consistency of kernel regression estimate,

 Annals of Statistics, vol. 12, no. 4, pp. 1570-1575, 1984.

 A. Krzyzak, and M. Pawlak,

Almost everywhere convergence of recursive regression function estimate and classification,

IEEE Transactions on Information Theory, vol. IT-30, no. 1, pp. 91-93, 1984.

 A. Krzyzak and M. Pawlak,

Distribution-free consistency of nonparametric kernel regression estimate and classification,

 IEEE Transactions on Information Theory, vol. IT-30, no. 1, pp. 78-81, 1984.

 A. Krzyzak and M. Partyka,

Application of systems analysis and  synthesis for optimal solutions of systems of differential equations,

 AMSE Review, vol. 3, no. 4, pp. 25-30, 1984.

 A. Krzyzak,

A classification procedure using multivariate variable kernel density estimate,

 Pattern Recognition Letters, vol. 1, no. 5,6, pp. 293-298, 1983.

A. Krzyzak and M. Pawlak,

Universal consistency results for Wolverton-Wagner regression function estimate with application in discrimination,

Problems of Control and Information Theory, vol. 2,  no. 1, pp. 32-42, 1983.

 W. Greblicki and A. Krzyzak,

Asymptotic properties of kernel estimates of a regression function,

Journal of Statistical Planning and Inference, vol. 4, pp. 81-90, 1980.

 W. Greblicki and A.  Krzyzak,

Nonparametric identification of memoryless system with cascade structure,

International Journal of Systems Science, vol. 10, pp. 1301-1310, 1979.

  Papers in Refereed Conference Proceedings:

 S. Li, T. Fevens, A. Krzyzak and Song Li,
Fast and robust clinical triple-region image segmentation using
one level set function,  Proceedings of the MICCAI 2006, 9th
International Conference on Medical Image Computing and Computer
Assisted Intervention, October 1-6, 2006, Copenhagen, Denmark.
Lecture Notes in Computer Science, Barillot, Christian, Haynor,
David R., Hellier, Pierre (Eds.), Vol. 0000, Springer-Verlag,
2006, pp. 0000.

 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Palmprint classification using dual-tree complex wavelets,
Proceedings of  IEEE International Conference on Image
Processing ICIP 2006, Atlanta, USA, Oct. 8-11, 2006, pp. 0000.

 M. Kohler and A. Krzyzak, Rate of convergence of local averaging plug-in
classification rules under margin condition,  Proceedings of
IEEE 2006 International Symposium on Information Theory, Seattle,
USA, July 9-14, 2006, pp. 2176-2179.



 A. Krzyzak and D. Schaefer, Nonlinear function learning
by the normalized radial basis function networks, to appear in
it Proceedings of 8th International Conference on Artificial
Intelligence and Soft Computing ICAISC'06, Zakopane, Poland, June
25-29, 2006. Lecture Notes in Artificial Intelligence, vol. LNAI
4029, Springer-Verlag, 2006, pp. 46-55.


 L. Jelen, T. Fevens and A. Krzyzak,
Automated feature extraction for breast cancer grading with
Bloom-Richardson scheme, to appear in it Proceedings of 20th
International Conference on Computer Assisted Radiology and
Surgery (CARS 2004), Osaka, Japan, June 28-July 1, 2006.


 S. Li, C. Jin, T. Fevens, A. Krzyzak, S. P. Mudur,
A medical volume reconstruction method using tetrahedral meshes
and level set, to appear in it Proceedings of 20th International
Conference on Computer Assisted Radiology and Surgery (CARS
2004), Osaka, Japan, June 28-July 1, 2006.


 S. Li, T. Fevens, and A. Krzyzak,
Toward automatic computer aided dental X-ray analysis using level
set method ,  Proceedings of the MICCAI 2005, 8th
International Conference on Medical Image Computing and Computer
Assisted Intervention, October 26-29, 2005, Palm Springs,
California, USA. Lecture Notes in Computer Science, Duncan, J.,
Gerig, G. (Eds.), Vol. 3750, Springer-Verlag, 2005, pp. 670-678.

 J. Dong, C. Y. Suen, and A. Krzyzak, Cursive word
skew/slant correction based on Radon transform,  Proceedings
of International Conference on Analysis and Recognition ICDAR
2005, Seoul, Korea, Aug. 29-Sept. 1, 2005, pp. 478-482.

 M. Kohler and A. Krzyzak, Rates of convergence for adaptive
regression estimates with multiple hidden layer feedforward neural
networks,  Proceedings of IEEE 2004 International Symposium on
Information Theory, Adelaide, Australia, Sept. 4-9, 2005, pp.
1436-1440.

 J. Dong, C. Y. Suen, and A. Krzyzak, Algorithms of fast
SVM evaluation based on subspace projection,  Proceedings of
the International Joint Conference on Neural Networks IJCNN 2005,
Montreal, Canada, July 31-August 4, 2005, pp. 865-870.

 J. Dong, A. Krzyzak, and C. Y. Suen,
Low-level cursive word representation based on geometric
decomposition,  Proceedings of the International Conference on
Machine Learning and Data Mining, MLDM 2005, P. Perner and A.
Imiya (Eds.), Leipzig, Germany, July 9-11, 2005, Springer Lecture
Notes in Artificial Intelligence, vol. LNAI 3587, pp. 590-599,
2005.


 S. Li, T. Fevens, A. Krzyzak, and S. Li,
Automatic clinical image segmentation using pathological
modelling, PCA and SVM,  Proceedings of the International
Conference on Machine Learning and Data Mining, MLDM 2005, P.
Perner and A. Imiya (Eds.), Leipzig, Germany, July 9-11, 2005,
Springer Lecture Notes in Artificial Intelligence, vol. LNAI 3587,
pp. 314-324, 2005.


 A. Krzyzak, J. Sasiadek and B. Kegl,
On the Hermite Series Approach to Nonparametric Identification of
Hammerstein Systems,  Proceedings of IFAC World Congress,
Prague, July 4-8, 2005 (to appear).

 S. Li, T. Fevens, and A. Krzyzak,
Level set segmentation for computer-aided dental x-ray analysis,
Proceedings of  SPIE Symposium on Medical Imaging, San Diego,
USA, February 12-17, 2005, pp. 580-589.


 S. Li, T. Fevens, and A. Krzyzak,
Image segmentation adapted for clinical settings by combining
pattern classification and level sets, Proceedings of the em
MICCAI 2004, 7th International Conference on Medical Image
Computing and Computer Assisted Intervention, September 26-30,
2004, Saint-Malo, France. Lecture Notes in Computer Science, vol.
LNCS 3216-3217, Springer-Verlag, pp. 160--167, 2004.


 M. Kohler and A. Krzyzak,
Adaptive regression estimation with multilayer
feedforward neural networks,  Proceedings of the
6-th World Congress of the Bernoulli Society for Mathematical
Statistics and Probability, Barcelona, Spain, July 26-31, 2004,
p. 129.

 M. Kohler and A. Krzyzak,
Adaptive regression estimation with multilayer
feedforward neural networks,  Proceedings of
IEEE 2004 International Symposium on Information Theory,
Chicago, USA, June 29-July 4, 2004, p. 467.


 S. Li, T. Fevens, and A. Krzyzak,
An SVM-based framework for autonomous volumetric medical image
segmentation using hierarchical and coupled level sets,
Proceedings of  18th International Conference on Computer
Assisted Radiology and Surgery (CARS 2004), Chicago, USA, June 23
- 26, 2004, Elsevier Int. Congress Series 1268, 2004, pp.
207--212.

 A. Krzyzak and E. Skubalska-Rafajlowicz,
Combining space-filling curves and radial basis function networks,
Proceedings of  ICAISC 2004, 7th International Conference on
Artificial Intelligence and Soft Computing, June 7-11, 2004,
Zakopane, Poland. Lecture Notes in Artificial Intelligence, vol.
LNAI 3070, Springer-Verlag, 2004, pp. 229-234.


 R. Buchnajzer, J. W. Atwood, and A. Krzyzak,
Simulation of lead-time scheduling in PMP FWA networks,
Proceedings of  2004 IEEE Canadian Conference on Electrical
and Computer Engineering (CCECE 2004), Niagara Falls, May 2-5,
2004, pp. 1693--1698.


 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Image compression with optimal wavelet, Proceedings of  2004 IEEE Canadian
Conference on Electrical and Computer Engineering (CCECE 2004),
Niagara Falls, May 2-5, 2004, pp. 0209--0212.


 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Image denoising using neighboring wavelet coefficient,
Proceedings of  IEEE International Conference on Acoustics,
Speech and Signal Processing ICASSP 2004, Montreal, May 17-21,
2004, pp. II-917-920.


 A. Krzyzak and S. Klasa,
Chernoff bound on classification error for multivariate parametric
and nonparametric classes, Proceedings of the  35th
Southeastern International Conference on Combinatorics, Graph
Theory, and Computing, Baton Rouge, Florida, March 8-12, 2004.

 G. Y. Chen, T. D. Bui, and A. Krzyzak,
Optimal Wavelets and Neural Networks for Pattern Recognition, em
Proceedings of Image and Vision Computing, Palmerston North, New
Zealand, November 26-28, 2003, pp. 315-319.


 J. Dong, A. Krzyzak, and C. Y. Suen,
High accuracy handwritten Chinese character recognition
using support vector machine,
 Proceedings of International Workshop on Artificial Neural
Networks in Pattern Recognition,
Florence, Italy, September 12-13, 2003, pp. 39-45.


 A. Krzyzak and D. Schaefer, Nonparametric regression estimation
by radial basis function networks and empirical risk minimization,
 Proceedings of 2003 9th IEEE International Conference on
Methods and Models in Automation and Robotics (MMAR 2003),
Miedzyzdroje, Poland, August 25-28, 2003, pp. 891-898.

 A. Krzyzak and D. Schaefer, Nonparametric regression
estimation by normalized radial basis function networks, em
Proceedings of IEEE 2003 International Symposium on Information
Theory, Yokohama, Japan, June 29-July 4, p. 219, 2003.

 J. Dong, A. Krzyzak, and C. Y. Suen,
A fast parallel optimization for training support vector, em
Proceedings of the International Conference on Machine Learning
and Data Mining, MLDM 2003, P. Perner and A. Rosenfeld (Eds.),
Leipzig, Germany, July 5-7, 2003, Springer Lecture Notes in
Artificial Intelligence, vol. LNAI 2734, pp. 96-105, 2003.

 J. Dong, A. Krzyzak, and C. Y. Suen,
A practical SMO algorithm,  Proceedings of the 2002
International Conference on Pattern Recognition, Quebec City,
Canada, August 11-15, 2002.

 J. Dong, A. Krzyzak, and C. Y. Suen,
A fast SVM training algorithm,  Proceedings of the
International Workshop on Pattern Recognition with Support Vector
Machines , S. W. Lee and A. Verri (Editors). Niagara Falls,
Canada, August 10, 2002. Springer Lecture Notes in Computer
Science LNCS, vol. LNCS 2388, pp. 53-67, 2002.


 M. Pawlak, E. Rafajlowicz, and A. Krzyzak,
Post-filtering versus pre-filtering for signal sampling and
recovery under noise,  IEEE International Symposium on
Information Theory, Lausanne, Switzerland, June 30-July 5, p.
155, 2002.

 A. Krzyzak and S. Klasa,
On convergence of neural network
regression estimates and
classification rules, Proceedings of the
30th Southeastern International Conference on
Combinatorics, Graph Theory, and Computing, Baton
Rouge, Florida, 2001,  Congressus
Numerantium, vol. 152, pp. 159-168, 2002.
 

 J. Dong, A. Krzyzak, and C. Y. Suen,
A multinet local learning framework for pattern recognition,
 Proceedings of the Sixth International Conference on Document Analysis and Recognition,
Seattle, September 10-13, 2001, pp. 328-332, 2001.


 J. Dong, A. Krzyzak, and C. Y. Suen,
A local learning framework for recognition of lowercase handwritten characters,
 Proceedings of Machine Learning and Data Mining in Pattern Recognition Conference,
Leipzig, July 25-27, 2001, Springer Lecture Notes in Computer Science, pp. 226-238, 2001.

 A. Krzyzak,
Nonlinear function learning and classification using optimal radial basis function networks,
 Proceedings of Machine Learning and Data Mining in Pattern Recognition Conference,
Leipzig, July 25-27, 2001, Springer Lecture Notes in Computer Science, pp. 217-225, 2001.

 A. Krzyzak,
Nonlinear function learning and classification using optimal radial basis function networks,
presented at the  Conference on Nonlinear Learning and Classification, Mathematical Sciences Research Institute, University of California at Berkeley, March 19-29, 2001, considered for the proceedings
to be published in Springer Lecture Notes in Computer Science.

 A. Krzyzak,
Nonlinear function learning
using optimal radial basis function networks,
 Proceedings of IEEE International Symposium on Information Theory, Washington DC, June 24-29, 2001, p. 93.

 J. Dong, A. Krzyzak, and C. Y. Suen,
A local learning framework for pattern recognition,
 Proceedings of 14th Conference Vision Interface, Ottawa, Canada, June 7-9, 2001, pp. 220--227.


 A. Krzyzak and S. Klasa, On
almost sure convergence and rates of radial basis function networks classifiers,  

Congressus Numerantium, vol. 142, 2000, pp. 185-193.


 J. Zhou, A. Krzyzak, and C. Y. Suen,
Recognition and verification of touching handwritten numerals,
 Proceedings of the International Workshop on Frontiers in Handwriting Recognition, Amsterdam, September 11-13, 2000, pp. 179-188.

 J. Zhou, A. Krzyzak, and C. Y. Suen,

Recognition and Verification of Touching Handwritten Numerals,

Proceedings of the International Workshop on Frontiers in Handwriting Recognition, Amsterdam, September 11-13, 2000,  pp. 179-188.

 B. Kegl, A. Krzyzak, and H. Niemann,

  Radial Basis Function Networks and Complexity Regularization   in Function Learning and Classification, 

  Proceedings of the 15th International Conference on Pattern Recognition, vol. 2, Barcelona, September 4-8, 2000, pp. 81-86.

 B. Kegl, A. Krzyzak, 

Piecewise linear skeletonization using principal curves,

  Proceedings of the 15th International Conference on Pattern  Recognition, vol. 3, Barcelona, September 4-8, 2000, pp. 135-138.

 A. Krzyzak, E. Rafajlowicz, and M. Pawlak,

Signal Recovery Under Noise for Not Necessarily  Band-Limited Signals from Noisy Observations,  Proceedings of  2000 IEEE  International Symposium on Information Theory, Sorrento, June 23-30, 2000 p. 360.

 E. Rafajlowicz and A. Krzyzak,

Consistency of max+min algorithm for reconstruction of surfaces from random depth sensing data,  Proceedings of the Fifth Conference on Neural Networks and Computing, Zakopane, Poland, June 6-10, 2000, pp. 150-155.

 E. Rafajlowicz and A. Krzyzak,

Reconstruction of surfaces from random depth sensing using RBF-like nets, 

Proceedings of the Fifth Conference on Neural Networks and Computin, Zakopane, Poland, June 6-10, 2000, pp. 156-161.

 M. Kohler, and A. Krzyzak, 

A Vapnik-Chervonenkis approach   to penalized least squares estimation,

Abstracts of the 5th World Congress of the Bernoulli Society for Probability and Mathematical Statistics and 63rd Annual Meeting of the Institute of Mathematical Statistics (IMS), Guanajuato,   Mexico, 15-20 May, 2000.

 A. Krzyzak and S. Klasa,  

On $L_1$ convergence and rates of generalized radial basis function networks in nonlinear estimation

  and classification, 

Congressus Numerantium, vol. 138,   pp. 119-127, 1999.

 L. Devroye and A. Krzyzak,

On Hilbert kernel density estimates,

  Proceedings of the Colloquium on Limit Theorems in Probability and Statistics, Balatonlelle, Hungary, p. 22, 1999.

 B. Kegl, A. Krzyzak, T. Linder, and K. Zeger,

 A Polygonal Line Algorithm for Constructing Principal Curves,

 Advances in  Neural Information  Processing Systems NIPS'98, MIT Press, vol. 11, pp. 501--507, 1999.

 B. Kegl, A. Krzyzak, T. Linder, and K. Zeger, Principal

    Curves: Learning and  Convergence, Proceedings of 1998 IEEE  International Symposium on Information Theory, Boston, p. 387, 1998.

 A. Krzyzak, M. Pawlak, and E. Rafajlowicz,

Signal Recovery Under Noise for Not Necessarily  Band-Limited Functions,  

Proceedings of 1998 IEEE  International Symposium on Information Theory, Boston, p. 477, 1998.

 J. Zhou, Q. Gan, A.  Krzyzak, and C.Y. Suen, 

Quantum Neural Network in Recognition of Handwritten Numerals,

Proceedings of International Workshop on  Frontiers in Handwriting Recogntion IWFHR'98, Taejon, Korea, pp. 305-314, 1998.

B. Kegl, A. Krzyzak, and H. Niemann, 

Radial Basis Function   Networks in Nonparametric Classification and  Learning, 

  Proceedings of the 14th International Conference on Pattern   Recognition, Brisbane, pp. 565-570, 1998.

A. Krzyzak,  and J. Sasiadek,

Identification of dynamic nonlinear systems using the Hermite series approach,  

Proceedings of 1997 IEEE International   Conference on Decision and Control, San Diego, pp. 733-736 , 1997.

A. Krzyzak, S. Klasa and L. Xu,

On asymptotic properties of radial basis regression function estimates and classification rules,  Congressus Numerantium, vol. 126, pp. 123-128, 1997.

 E. Rafajlowicz, A. Krzyzak, and M. Pawlak, 

Moving average   restoration of band-limited signals from noisy observations,

Proceedings of 1997 IEEE International Symposium on Information Theory,

Ulm, Germany,  p. 243, 1997.

A. Krzyzak, and T. Linder, Radial basis function networks and complexity regularization in function learning,

 Proceedings of Neural Information Processing Systems NIPS'96, Denver, pp. 197-203, 1996.

 A. Krzyzak and J.A. Nossek,

Adaptive radial basis function nets for classification and nonlinear function estimation,

Proceedings of the World Congress on Neural Networks,

San Diego, pp. 271-276, 1996.

A. Krzyzak and A. Cichocki, 

On the convergence of the recursive radial basis function networks,  

Proceedings of the World Congress on Neural Networks, San Diego, pp. 239-244, 1996.

A. Krzyzak and H. Niemann,  

On MISE convergence rates of radial basis function networks,  

Proceedings of 1996 IEEE International Conference on Neural Networks, Washington, DC, pp. 235-240, 1996.

 E. Skubalska-Rafajlowicz and A. Krzyzak,

Fast k-NN classification rule using metrics on space-filling curves, 

Proceedings of the 13th International Conference on Pattern Recognition, Part B,

Vienna, Austria, pp. 121-124, 1996.

A. Krzyzak, 

On the convergence of the recursive radial basis function networks,  

Proceedings of the Second Conference on Neural Networks and Their Applications, Szczyrk, Poland,

pp. 292-299, 1996.

 A. Krzyzak and T. Linder, 

Radial basis function networks and nonparametric classification: complexity regularization and the rates of  convergence,  

Proceedings of the 13th International Conference on Pattern Recognition, Part D,

Vienna, Austria, pp. 650-653, 1996.

  A. Krzyzak and T. Linder, 

Radial basis function networks and complexity regularization in function learning, 

Proceedings of 1996 IEEE Workshop on Information Theory,  Haifa, Israel, p. 63, 1996.

 A. Krzyzak and  T. Linder, 

Nonlinear function estimation using radial basis function networks and complexity regularization, 

Proceedings of 6th International Conference on Mathematical Statistics,  Jachranka, Poland, pp. 29-30, 1996.

 A. Krzyzak,  

On optimal radial basis function nets and nonlinear function estimates, 

Proceedings of 1995 IEEE International Conference on Neural Networks, Perth, Australia, pp. 2243-2246, 1995.

 A. Krzyzak, S. Klasa, and L. Xu,  

On L1 convergence rate of RBF networks and kernel regression estimators with applications in

classification,  

Proceedings of 1995 IEEE International Conference on Neural Networks, Perth, Australia, pp. 265-269, 1995.

 E. Skubalska-Rafajlowicz and A. Krzyzak, 

Data sorting along a space-filling curve for fast pattern recognition,  

Proceedings of the Second International Symposium on Methods and Models in Automation

and Robotics, Miedzyzdroje, Poland, pp. 339-344, 1995.

 A. Krzyzak, T. Linder, and G. Lugosi, 

Nonparametric estimation and classification using radial basis function nets and empirical risk minimization,  

Proceedings of 1995 IEEE International Symposium on Information Theory, Whistler, p. 258, 1995.

 A. Krzyzak, E. Rafajlowicz, and M. Pawlak,

On reconstruction of band-limited signals from noisy measurements,

 Proceedings of 1994 IEEE International Conference on Decision and Control,

Orlando, pp. 1195-1196, 1994.

 A. Krzyzak and J. Sasiadek,

Identification of dynamic nonlinear systems using the Hermite series approach,  

Proceedings of 1994 IEEE International Conference on Decision and Control, Orlando, pp. 1731-1732, 1994.

 A. Krzyzak, T. Linder and G. Lugosi,

Nonparametric  classification using radial basis function nets and empirical  risk minimization,  

Proceedings of the 12th International Conference on Pattern Recognition, Jerusalem, Israel, pp. 72-76, 1994.

 A. Krzyzak, L. Xu and S. Klasa,

On $L_1$ convergence rates of RBF networks and kernel regression estimators with applications in classification,

Proceedings of the 12th International Conference on Pattern Recognition, Jerusalem, Israel, pp. 364-366, 1994.

 E. Rafajlowicz, A. Krzyzak, and M. Pawlak,

On restoration of band-limited signals from noisy observations,

 Proceedings of 1994 IEEE International Symposium on Information Theory, Trondheim, Norway, p. 127, 1994.

A. Krzyzak, L. Xu, and H. Niemann,

On $L_2$ convergence rates of radial basis function networks and kernel regression estimates,

 Proceedings of 1994 IEEE International Symposium on Information Theory, Trondheim, Norway, p. 37, 1994.

  A. Krzy.zak,  

On identification of cascade systems by nonparametric techniques with applications to pollution spread modeling in the river systems,

Proceedings of the International Conference on Stochastic and Statistical Methods in Hydrology and Environmental Engineering, Kluwer Academic Publishers, Dordrecht, Netherlands, 1994.

 A. Krzyzak,  and R. Unbehauen,

On estimation of nonlinear systems by nonparametric techniques, 

Proceedings of IEEE International Conference on Circuits and Systems, London, pp. 189-192, 1994.

 P. Scattolin and A. Krzy.zak, 

Weighted elastic matching method   for recognition of handwritten numerals, 

Proceedings of the   Vision Interface'94 Conference, Banff, Canada, pp. 178-185, 1994.

N.W. Strathy, C.Y. Suen, and A.  Krzyzak,

Segmentation of handwritten digits using contour features,

 Proceedings of the Second International Conference on Document Analysis and Recognition, Tsukuba Science City, Japan, pp.577-580, 1993.

 N.W. Strathy, C.Y. Suen, and A. Krzyzak,

 Segmentation of connected digits using contour regions and corner points,

Proceedings of International Conference on Signal Processing, Beijing, China, pp. 1046-1049, 1993.

 X. Yu, T.D. Bui, and A. Krzyzak,

The genetic algorithm parameter settings for robust estimation and range segmentation and fitting,

 Proceedings of the 8th Scandinavian Conference on Image Analysis, Tromsoe, Norway, pp. 623-630, 1993.

L. Xu, A. Krzyzak, and A. Youille,

On radial basis function net and kernel regression: approximation ability, convergence rate and receptive field size,

 Proceedings of 1993 IEEE International Symposium on Information Theory, p. 353, 1993.

 L. Xu, A.  Krzyzak, and A. Youille,

Kernel regression and radial basis functions net: some theoretical studies, 

Proceedings of the International Joint Conference on Neural Network, Baltimore, MD., 1992.

 L. Xu, A.  Krzyzak, and E. Oja,

Rival penalized competitive learning for cluster analysis, RBF net and curve detection,  

Proceedings of the 11th International Conference on Pattern Recognition, The Hague, pp.

496-499, 1992.

 X. Yu, T.D. Bui, and A. Krzyzak, 

3-D object recognition and pose determination by quadratic surface invariants, 

Ed. C. Arcelli et al.,  Proceedings of the International Workshop on Visual Form, Capri, Plenum Press, New York, pp. 623-632, 1992.

  X. Yu, T.D. Bui, and A. Krzyzak,

3D range image segmentation and filtering by quadratic surfaces,

 Proceedings of SPIE Conference on Advances in Intelligent  Robotic Systems, Boston, 1991.

P. Zhu, A. Krzyzak,  and T. Kasvand,

Recovering motion from image range sequences,

Proceedings of SPIE Conference on Advances in Intelligent Robotic Systems, Boston, pp. 1611-1623, 1991.

P. Zhu, T. Kasvand, and A.  Krzyzak,

Range image segmentation based on coherent motion,

 Proceedings of the 14th Symposium on Information Theory and its Applications, SITA-91, Ibusuki, Japan, pp. 563-566, 1991.

A. Krzyzak, and  J.Z. Sasiadek,

Flexible robot identification using nonparametric techniques,

Proceedings of the 30th IEEE Conference on Decision and Control, Brighton, pp. 146-147, 1991.

 A. Krzyzak and P. Wojcik,

Nonparametric estimation of discrete-type Hammerstein systems with applications to tactile sensors identification,  

Proceedings of the 30th IEEE Conference on Decision and Control, Brighton, pp. 676-677, 1991.

A. Krzyzak,  

On exponential bounds on the Bayes risk of the nonparametric classification rules, 

Proceedings of the NATO Advanced Science Institute, Spetses, Greece, 1990.

 A. Krzyzak, W. Dai,  and C.Y. Suen,

On the recognition of handwritten characters using neural networks,

Eds. R. Plamondon and H.D. Cheng, World Scientific, pp. 115-135, 1991.

 X. Yu, T.D. Bui,  and A. Krzyzak,

Segmentation and fitting by residual,

 Proceedings of the Canadian Conference on Electrical and Computer Engineering, Quebec City, Quebec, 4.5.1-4.5.4, 1991.

P.Y. Zhu, A. Krzyzak, and T. Kasvand,

The local measurement and global interpretation of 3D motion field generated by several moving objects

from range image sequences,

 Proceedings of the Canadian Conference on Electrical and Computer Engineering, Quebec City, Quebec, 20.1.1-20.1.4, 1991.

 M. Pawlowsky, and A. Krzyzak,

Desegregation in genetic algorithms,

 Proceedings of the Canadian Conference on Electrical and Computer Engineering, Quebec City, Quebec, 55.3.1-55.3.4, 1991.

 X. Yu, T.D. Bui, and A. Krzyzak,

3-D object recognition and pose determination by quadratic surface invariants,  

Proceedings of the 7th International Scandinavian Conference on Image Analysis, Aalborg, Denmark, 1991.

L. Xu, L., A. Krzyzak, and C.Y. Suen,

Associative switch for combining multiple classifiers,

Proceedings of the International Joint Conference on Neural Networks, Seattle, I43-I48, 1991.

L. Xu, A.  Krzyzak,  and E. Oja,

Neural-net method for dual subspace pattern recognition,

Proceedings of the International Joint Conference on Neural Networks, Seattle, II-379-384, 1991.

A. Krzyzak,

Nonparametric identification of discrete-time Hammerstein systems,

Proceedings of the 9th IFAC/IFORS Symposium on Identification and System Parameter Estimation, Budapest, 725-730, 1991.

 A. Krzy.zak,

On exponential bounds on the Bayes risk of nonparametric classification rules, 

Proceedings of the 1991 International Symposium on Information Theory, Budapest, 289, 1991.

 L. Xu, and A. Krzyzak,

Curve detection by rival penalized competitive learning,

Proc. of the International Conference on Neural Networks for Vision and Image Processing, Wang Institute, p. 64, 1991.

 A. Krzyzak, W. Dai, and C.Y. Suen,

Classification of large set of handwritten characters using modified back propagation model,

 Proc. of the International Joint Conference on Neural Networks, San Diego, 225-232, 1990.

P.Y. Zhu, T. Kasvand, and A.  Krzyzak,

Motion estimation based on point correspondence using neural network,  

Proc. of the International Joint Conference on Neural Networks, San Diego, 869-874, 1990.

 A. Krzyzak, and J. Sasiadek,

Dynamics identification of a flexible robot using multichannel nonlinear systems, 

Proceedings of the American Control Conference, San Diego, 1232-1236, 1990.

A. Krzyzak,

On estimation of discrete Hammerstein systems by the Fourier and Hermite series estimates,  

Proceedings of the IEEE International Symposium on Information Theory, San Diego, p. 113, 1990.

A. Krzyzak,

On estimation of discrete Hammerstein systems by the recursive kernel regression estimates, 

Proceedings of the IEEE International Symposium on Information Theory, San Diego, 113, 1990.

A. Krzyzak,

On identification of nonstationary Hammerstein systems by the Fourier series regression estimate, 

Proceedings of the 28th IEEE Conference on Decision and Control, Tampa, 626-629, 1989.

A. Krzyzak, and J. Sasiadek,

Displacement identification of flexible manipulator arm using Hammerstein model, 

Proceedings of the American Control Conference, Pittsburgh, 2360-2363, 1989.

A. Krzyzak, and J. Sasiadek,

Identification of Hammerstein systems by the Hermite series estimate with applications to a flexible robot manipulator control,

 Proceedings of the IEEE International Conference on Control and Applications, Jerusalem, 1989.

A. Krzyzak, S.Y. Leung,  and C.Y. Suen,

Reconstruction of two dimensional patterns by Fourier descriptors,

 Proceedings of the 9th International Conference on Pattern Recognition,  Rome, 555-558, 1988.

A. Krzyzak, S.Y. Leung,  and C.Y. Suen,

Fourier descriptors of two dimensional shapes-reconstruction and accuracy,

Proceedings of the IAPR Workshop on Computer Vision-Special Hardware and Industrial Applications, Tokyo, 199-202, 1988.

A. Krzyzak,

On identification of discrete Hammerstein system by the Fourier series regression estimate,  

Proceedings of the American Control Conference, Atlanta, 1321-1324, 1988.

A. Krzyzak,

On estimation of the class of nonlinear systems by the kernel regression estimate, 

Proc. of the IEEE International Symposium on Information Theory, Kobe, 96, 1988.

A. Krzyzak and H. El-Buaeshi,

On classification of digitized contours via curve signatures,

 Proc. of the Vision Interface 88 Conference, Edmonton, 64-69, 1988.

A. Krzyzak,

On estimation of a discrete Hammerstein system by the kernel regression estimate,  

Proc. of the 26th Conference on Decision and Control, Los Angeles, 1897-1901, 1987.

 A. Krzyzak, P. Ahmed, and C.Y. Suen,

Recognition of totally unconstrained handwritten zipcodes by kernel techniques,  

Proc. of the 5th Scandinavian Conference on Image Analysis, Stockholm, 571-579, 1987.

A. Krzyzak, A. and H. El-buaeshi,

Classification of digitized curves represented by signatures,

Proc. of the 3rd International Symposium on Handwriting and Computer Applications, Montreal, 86-88, 1987.

 A. Krzyzak,

Optimal modeling and recursive identification of cascade systems,

 Proc. of the American Control Conference, Minneapolis, 1168-1173, 1987.

 A. Krzyzak,

On identification of discrete, multivariate Hammerstein system by kernel regression estimate,  

Proc. of the American Control Conference, Minneapolis, 1174-1180, 1987.

 A. Krzyzak,

The rates of convergence of k-NN classification rules, 

Proc. of the 8th International Conference on Pattern Recognition, Paris, 524-526, 1986.

 A. Krzyzak,

Nonparametric identification of a memoryless stochastic system with cascade structure,  

Proc. of the American Control Conference, Seattle, 1270-1273, 1986.

 A. Krzyzak and M. Partyka,

The rate of convergence of nonparametric discrimination rules derived from the kernel estimates of a regression function,

 Proc. of the 13th IASTED International Conference Modeling and Simulation, Lugano, 9-12, 1985.

A. Krzyzak,

Simulation analysis of performance of selected algorithms for nonparametric identification of a stochastic system with cascade structure, 

Proc. of the 4th IASTED International Symposium Modeling, Identification and Control, Grindelwald, 10-14, 1985.

A. Krzyzak,

A., Empirical evaluation of performance of multivariate variable kernel and k-NN classification rules,  

Proceedings of the 6th International Conference on Pattern Recognition, Montreal, 920, 1984.

A. Krzyzak,

Distribution-free consistency and the rates of convergence of kernel classification rules,  

Proceedings of the 6th International Conference on Pattern Recognition, Montreal, 921-923, 1984.

A. Krzyzak and W. Greblicki,

On a new algorithm for nonparametric identification of a stochastic system with cascade structure,  

Proceedings of the 15th Annual Pittsburgh Conference on Modelling and Simulation, Pittsburgh,

765-770, 1984.

A. Krzyzak,

A classification procedure using Breiman variable kernel density estimate,  

The 2nd International Conference on Pattern Recognition, Oxford, 1983 (published in Pattern Recognition Letters).

A. Krzyzak and M. Partyka,

Application of systems analysis and synthesis for optimal solutions of systems of differential equations, 

Proceedings of the International AMSE Summer Conference on Modeling and Simulation,

Nice, 39-42, 1983.

A. Krzyzak,

Distribution-free consistency and the rate of convergence of k-NN regression estimates,  

The 4th Panonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, 1983

(published in Muttenkungsblatt der Osterreichischen Statistischen Gasellschaft).

A.  Krzyzak and W. Greblicki,

Optimal modeling and identification of stochastic system with cascade structure, 

Proceedings of the 14th Annual Pittsburgh Conference on Modeling and Simulation, Pittsburgh, 361-365, 1983.

A. Krzyzak and M. Pawlak,

Almost everywhere convergence of recursive kernel regression function estimates,  

Proceedings of the 2nd  Panonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, Reidel Publishing Company, 191-209, 1982.

A. Krzyzak and M. Pawlak,

Estimation of multivariate density by orthogonal series,

Proceedings of the 2nd Panonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, Reidel Publishing Company, 211-221, 1981.

A.  Krzyzak and W. Greblicki,

Optimal model of stochastic systems with cascade structure and its application in simulation of water as well as industrial systems,

 Proceedings of the AMSE Conference on Modelling and Simulation, Paris, France, 1982.

A. Krzyzak,

Universal consistency and the rate of convergence of discrimination rules derived from recursive Parzen kernel estimates,

Proceedings of the 6th International Conference on Pattern Recognition, Munich, Germany, 1215, 1982.

A. Krzyzak,

Nonparametric identification of stochastic systems with cascade structure,  

Proceedings of the 8th National Conference on Automatization, Szczecin, Poland, 75-83, 1980 (in Polish).

Books:

L. Gyorfi, M. Kohler, A. Krzyzak, and H. Walk,
A Distribution-free Theory of Nonparametric Regression.
Springer-Verlag, ISBN: 0-387-95441-4, 2002.

 A. Krzyzak, T. Kasvand,  and C.Y. Suen, (Eds.).

Computer Vision and Shape Recognition.

World Scientific Publishers, 1989.

Book Chapters:

 J. Dong, A. Krzyzak, and C. Y. Suen,
Low-level cursive word representation based on geometric
decomposition,  Proceedings of the International Conference on
Machine Learning and Data Mining, MLDM 2005, P. Perner and A.
Imiya (Eds.), Leipzig, Germany, July 9-11, 2005, Springer Lecture
Notes in Artificial Intelligence, vol. LNAI 3587, pp. 590-599,
2005.


 S. Li, T. Fevens, A. Krzyzak, and S. Li,
Automatic clinical image segmentation using pathological
modelling, PCA and SVM,  Proceedings of the International
Conference on Machine Learning and Data Mining, MLDM 2005, P.
Perner and A. Imiya (Eds.), Leipzig, Germany, July 9-11, 2005,
Springer Lecture Notes in Artificial Intelligence, vol. LNAI 3587,
pp. 314-324, 2005.

 S. Li, T. Fevens, and A. Krzyzak,
Image segmentation adapted for clinical settings by combining
pattern classification and level sets, Proceedings of the
MICCAI 2004, 7th International Conference on Medical Image
Computing and Computer Assisted Intervention, September 26-30,
2004, Saint-Malo, France. Lecture Notes in Computer Science, vol.
LNCS 3216-3217, Springer-Verlag, pp. 160--167, 2004.

 S. Li, T. Fevens, and A. Krzyzak, An SVM-based framework
for autonomous volumetric medical image segmentation using
hierarchical and coupled level sets, Proceedings of  18th
International Conference on Computer Assisted Radiology and
Surgery (CARS 2004), Chicago, USA, June 23 - 26, 2004, Elsevier
Int. Congress Series 1268, 2004, pp. 207--212.

 A. Krzyzak and E. Skubalska-Rafajlowicz,
Combining space-filling curves and radial basis function networks,
Proceedings of  ICAISC 2004, 7th International Conference on
Artificial Intelligence and Soft Computing, June 7-11, 2004,
Zakopane, Poland. Lecture Notes in Artificial Intelligence, vol.
LNAI 3070, Springer-Verlag, 2004, pp. 229-234.


 J. Dong, A. Krzyzak, and C. Y. Suen,
A Fast Parallel Optimization for Training Support Vector,
Proceedings of the Third International Conference on Machine Learning and
Data Mining, MLDM 2003, Leipzig, Germany, July 5-7, 2003.
Springer Lecture Notes in Computer Science LNAI, pp. 96-105, 2003.

 A. Krzyzak, Nonlinear function learning
and classification using optimal radial basis function networks,
Nonlinear Learning and Classification.  Proceedings of the
International Workshop on Nonlinear Estimation and Learning,
Eds. David D. Denison, Mark H. Hansen, Christopher C. Holmes,
Bani Mallick and Bin Yu. Mathematical Sciences Research Institute,
University of California at Berkeley, Berkeley, California,
March 19-29, 2001. Lecture Notes in Statistics LNS, vol. 171,
Springer-Verlag, pp. 393-404, 2002.

 J. Dong, A. Krzyzak, and C. Y. Suen, A fast SVM training algorithm,
 Proceedings of the International Workshop on
Pattern Recognition with Support Vector Machines,
Niagara Falls, Canada, August 10, 2002. Lecture Notes
in Computer Science LNCS, vol. 2388, Springer-Verlag,
New York, USA, pp. 53-67, 2002.
 

  L. Devroye and A. Krzyzak, 

A. Krzyzak and E. Rafajlowicz, 

Approximation of functions   using nonrecursive neural networks, 

Ed. W. Duch, J. Korbicz,   L. Rutkowski and R. Tadeusiewicz,  

Biocybernetics and Biomedical Engineering, Academic Publishing House Exit,   pp. 371--388, 2000.

J. Zhou,  Q. Gan, A. Krzyzak, and C.Y. Suen,  

Quantum Neural Network in Recognition of Handwritten Numerals,  

Ed. S.W. Lee, Advances in Handwriting Recogntion, World Scientific Publishing, Singapore, pp. 368-377, 1999.

B. Kegl, A. Krzyzak, T. Linder, and K. Zeger,

A Polygonal Line Algorithm for Constructing Principal Curves,

Ed. S. Solla,  Advances in   Neural Processing Systems 11, MIT Press, pp. 501-507, 1999.

A. Krzyzak and T. Linder, 

Radial basis function networks and

complexity regularization in function learning, 

Eds. M.C. Mozer, M.I. Jordan and T. Petsche,  Advances in   Neural Processing Systems 9, MIT Press, pp. 197-203, 1997.

P. Scattolin and A. Krzyzak, 

Weighted elastic matching method   for recognition of handwritten numerals, 

Eds. C. Archibaldt and P. Kwok,  Research in Computer and Robot Vision, World Scientific Publishing, Singapore, pp. 367-395, 1994.

  A. Krzyzak, 

On identification of cascade systems by nonparametric techniques with applications to pollution spread modeling in the river systems,

 Proceedings of the International Conference on Stochastic and Statistical Methods in Hydrology and Environmental Engineering, Kluwer Academic Publishers, Dordrecht, Netherlands, 1994.

 X. Yu, T.D. Bui and A. Krzyzak,

3D Object recognition and pose determination by quadratic surface invariants, 

Plenum Press, pp. 623-632, 1991.

A. Krzyzak,

On exponential bounds on the Bayes risk of the nonparametric classification rules, 

Ed. G. Roussas,  Nonparametric Functional Estimation, Kluwer, 347-360, 1991.

A. Krzyzak, W. Dai, and  C.Y. Suen,

On the recognition of handwritten characters using neural networks,

Eds. R. Plamondon and H.D. Cheng,  Pattern Recognition: Architectures, Algorithms and

Applications, World Scientific, pp. 115-135, 1991.

 A. Krzyzak, and H. El-Buaeshi,

Classification of digitized curves represented by signatures and

Fourier descriptors,  

Computer Vision and Shape Recognition, Singapore: World Scientific Publishing Co., Singapore, 241-260, 1989.

Book Reviews:

 Book review of  L.F. Luo and R. Unbehauen,  

Applied Neural Networks for Signal Processing, in  Signal Processing Journal,

64(3):397-399, 1998.

 Book review of  A. Cichocki and R. Unbehauen,  

Neural Networks for Optimization and Signal Processing, in  Archive fur Elektronik und Ubertragungstechnik, vol. 48, no. 2, p. 75, 1994.